Robert Kern wrote:
> On Fri, Jan 9, 2009 at 08:08, Neal Becker wrote:
>> Robert Kern wrote:
>>
>>> On Fri, Jan 9, 2009 at 06:05, Neal Becker wrote:
I'm working on interfacing to a custom FPGA board. The kernel driver
exposes the FPGA memory via mmap.
It might be nice to use
Hello again!
On Sat, Jan 10, 2009 at 7:11 AM, Rich E wrote:
> Well I see it works, however with one change: the %apply typemaps need
> to be done before %include'ing the header file, or else nothing in
> that header file will automatically get typemapped (only the functions
> that are written us
Chuck,
Thanks, your version is much faster. I would prefer a solution that
doesn't force me to re-implement weirdDistance (as my two solutions
were). But the function is so simple that it is easier just to re-write
it for speed as you did.
By the way, I came out with one more solution that looks
> Sturla Molden wrote:
>> For the same problems where you would use meshgrid in Matlab.
>
> well, I used to use meshgrid a lot because MATLAB could not do
> broadcasting. Which is probably why the OP has been trying to use it.
mgrid and ogrid are both meshgrids, with ogrid having a sparse
represen
On Fri, Jan 9, 2009 at 16:04, Christopher Barker wrote:
> Sturla Molden wrote:
>> For the same problems where you would use meshgrid in Matlab.
>
> well, I used to use meshgrid a lot because MATLAB could not do
> broadcasting. Which is probably why the OP has been trying to use it.
>
> A note for
Well I see it works, however with one change: the %apply typemaps need
to be done before %include'ing the header file, or else nothing in
that header file will automatically get typemapped (only the functions
that are written using %inline will be typemapped, which in the case
of the exampe you wro
Sturla Molden wrote:
> For the same problems where you would use meshgrid in Matlab.
well, I used to use meshgrid a lot because MATLAB could not do
broadcasting. Which is probably why the OP has been trying to use it.
A note for the docs:
The docs refer to ogrid and nd_grid, and as far as I can
>> However, just using the slices on the matrix instead of passing the
>> slices through ogrid is faster.
>
> So what is ogrid useful for?
For the same problems where you would use meshgrid in Matlab. That is
certain graphics problem for example; e.g. evaluating a surface z = f(x,y)
over a grid o
On Fri, Jan 9, 2009 at 15:40, Christopher Barker wrote:
> So what is ogrid useful for?
>
> Just curious...
Floating point grids.
x, y = ogrid[0:1:101j, 0:1:101j]
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad a
Robert Kern wrote:
> Instead, if you put both arguments into ogrid:
>
> In [4]: ogrid[0:5, 0:6]
> Out[4]:
> [array([[0],
>[1],
>[2],
>[3],
>[4]]),
> array([[0, 1, 2, 3, 4, 5]])]
>
> We get the kind of arrays you need. These shapes are compatible,
> through broadca
On Fri, Jan 9, 2009 at 08:25, Frédéric Bastien wrote:
> Hi,
>
> I would like to know how I can make a call to the blas function gemm in
> numpy. I need a multiply and accumulate for matrix and I don't want to
> allocate a new matrix each time I do it.
You can't in numpy. With scipy.linalg.fblas.d
On Fri, Jan 9, 2009 at 11:32, Nicolas ROUX wrote:
> Thanks !
>
> -1- The code style is good and the performance vs matlab is good.
> With 400x400:
> Matlab = 1.56 sec (with nested "for" loop, so no optimization)
> Numpy = 0.99 sec (with broadcasting)
>
>
> -2- Now with the code below I have s
On Fri, Jan 9, 2009 at 08:08, Neal Becker wrote:
> Robert Kern wrote:
>
>> On Fri, Jan 9, 2009 at 06:05, Neal Becker wrote:
>>> I'm working on interfacing to a custom FPGA board. The kernel driver
>>> exposes the FPGA memory via mmap.
>>>
>>> It might be nice to use numpy memmap to read/write da
On Fri, Jan 9, 2009 at 10:59, Neal Becker wrote:
> I modified memmap.py to avoid the issues with needed to read. It is working,
> but I am seeing these:
>
> m
> Exception exceptions.EnvironmentError: (22, 'Invalid argument') in method eos_memmap.__del__ of eos_memmap([255, 255, 255], dtype=uin
On Fri, Jan 9, 2009 at 11:45 AM, Paulo J. S. Silva wrote:
> Hello,
>
> I have a function that receives a array of shape (2,) and returns a
> number (a function from R^2 -> R). It basically looks like this:
>
>def weirdDistance2(x):
> return dot(dot(weirdMatrix, x), x)
>
> (weirdMatrix is
> -2- Now with the code below I have strange result.
> With w=h=400:
>- Using "slice"=> 0.99 sec
>- Using "numpy.ogrid" => 0.01 sec
It is not equivalent. The ogrid version only uses diagonal elements, and
does less work.
> It seems "ogrid" got better performance, but broadcas
Nicolas ROUX wrote:
> -2- Now with the code below I have strange result.
> With w=h=400:
> With w=400 and h=300:
>- Using "numpy.ogrid", => broadcast ERROR !
>
> The last broadcast error is:
> "ValueError: shape mismatch: objects cannot be broadcast to a single shape"
This is probably a br
Hello,
I have a function that receives a array of shape (2,) and returns a
number (a function from R^2 -> R). It basically looks like this:
def weirdDistance2(x):
return dot(dot(weirdMatrix, x), x)
(weirdMatrix is a "global" (2,2) array)
I want to see its level sets in the box [0, 1]
Thanks !
-1- The code style is good and the performance vs matlab is good.
With 400x400:
Matlab = 1.56 sec (with nested "for" loop, so no optimization)
Numpy = 0.99 sec (with broadcasting)
-2- Now with the code below I have strange result.
With w=h=400:
- Using "slice"=> 0.99 se
I modified memmap.py to avoid the issues with needed to read. It is working,
but I am seeing these:
m
Exception exceptions.EnvironmentError: (22, 'Invalid argument') in ignored
Exception exceptions.EnvironmentError: (22, 'Invalid argument') in ignored
Out[22]: eos_memmap([ 0, 0, 0, ...,
> I simplified the code to focus only on "what I" need, rather to bother you
> with the full code.
def test():
w = 3096
h = 2048
a = numpy.zeros((h,w), order='F') #Normally loaded with real data
b = numpy.zeros((h,w,3), order='F')
w0 = slice(0,w-2)
w1 = slice(1,w-1)
Sorry my previous mail was probalby not clear.
This mail was following the tread we had before, so with some discussion
legacy.
I simplified the code to focus only on "what I" need, rather to bother you
with the full code.
I wrote below a code closer to what I need, where you will agree that
vect
Hi,
I would like to know how I can make a call to the blas function gemm in
numpy. I need a multiply and accumulate for matrix and I don't want to
allocate a new matrix each time I do it.
thanks for your time
Frederic Bastien
___
Numpy-discussion maili
Robert Kern wrote:
> On Fri, Jan 9, 2009 at 06:05, Neal Becker wrote:
>> I'm working on interfacing to a custom FPGA board. The kernel driver
>> exposes the FPGA memory via mmap.
>>
>> It might be nice to use numpy memmap to read/write data. One issue is
>> that I think I will need to create th
> I understand the weakness of the missing JITcompiler in Python vs Matlab,
> that's why I invistigated numpy vectorization/broadcast.
> (hoping to find a cool way to write our code in fast Numpy)
>
> I used the page http://www.scipy.org/PerformancePython to write my code
> efficiently in Numpy.
>
Robert Kern wrote:
> On Fri, Jan 9, 2009 at 06:05, Neal Becker wrote:
>> I'm working on interfacing to a custom FPGA board. The kernel driver
>> exposes the FPGA memory via mmap.
>>
>> It might be nice to use numpy memmap to read/write data. One issue is
>> that I think I will need to create th
On Fri, Jan 9, 2009 at 06:05, Neal Becker wrote:
> I'm working on interfacing to a custom FPGA board. The kernel driver exposes
> the FPGA memory via mmap.
>
> It might be nice to use numpy memmap to read/write data. One issue is that I
> think I will need to create the memmap array from a fd,
I'm working on interfacing to a custom FPGA board. The kernel driver exposes
the FPGA memory via mmap.
It might be nice to use numpy memmap to read/write data. One issue is that I
think I will need to create the memmap array from a fd, not a file name. The
reason is I wrote the driver to onl
Hi !
Thanks a lot for your fast/detailed reply.
A very good point for Numpy ;-)
I spent all my time trying to prepare my testcase to better share with you,
that's why I didn't reply fast.
I understand the weakness of the missing JITcompiler in Python vs Matlab,
that's why I invistigated numpy ve
On Fri, Jan 9, 2009 at 03:27, Stéfan van der Walt wrote:
> 2009/1/9 Robert Kern :
>> try_run() is not the right thing to call for such a purpose. Use
>> FCompiler.get_version().
>
> That was just an example. What I want to do is run something like
> "pkg-config blah" and parse the output, but I g
2009/1/9 Robert Kern :
> try_run() is not the right thing to call for such a purpose. Use
> FCompiler.get_version().
That was just an example. What I want to do is run something like
"pkg-config blah" and parse the output, but I get the idea from
David's post that that is OK.
Cheers
Stéfan
_
Stéfan van der Walt wrote:
> 2009/1/9 David Cournapeau :
>
>>> What do you suggest as workarounds?
>>>
>> What about not using tests which need to run on the target platform :)
>>
>
> Let me simplify the question. How do you detect the version of the
> local Fortran compiler without
On Fri, Jan 9, 2009 at 02:31, Stéfan van der Walt wrote:
> 2009/1/9 David Cournapeau :
>>> What do you suggest as workarounds?
>>
>> What about not using tests which need to run on the target platform :)
>
> Let me simplify the question. How do you detect the version of the
> local Fortran compil
2009/1/9 David Cournapeau :
>> What do you suggest as workarounds?
>
> What about not using tests which need to run on the target platform :)
Let me simplify the question. How do you detect the version of the
local Fortran compiler without executing the compiler? Or is that OK,
and you'd simply
Stéfan van der Walt wrote:
> 2009/1/9 David Cournapeau :
>
>> It happened that in that particular case where it is used in numpy, I
>> found a way around it, but I would like to get rid of it completely at
>> some point.
>>
>
> What do you suggest as workarounds?
>
>
What about not usin
2009/1/9 David Cournapeau :
> It happened that in that particular case where it is used in numpy, I
> found a way around it, but I would like to get rid of it completely at
> some point.
What do you suggest as workarounds?
Stéfan
___
Numpy-discussion ma
2009/1/9 David Cournapeau :
> As Robert said, BTS is supposedly a better system for this for this kind
> of things - but at least for me, trac is so slow and painful to use that
> I try to avoid it as much as possible.
We are running Trac 10.2 from November 2006, so it is quite possible
that some
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